We develop new quasi-experimental tools to understand algorithmic discrimination and build non-discriminatory algorithms when the outcome of interest is only selectively observed. These tools are applied in the context of pretrial bail decisions, where conventional algorithmic predictions are...

In this article, we review a growing empirical literature on the effectiveness and fairness of the US pretrial system and discuss its policy implications. Despite the importance of this stage of the criminal legal process, researchers have only recently begun to explore how the pretrial system...

Human decision-makers frequently override the recommendations generated by predictive algorithms, but it is unclear whether these discretionary overrides add valuable private information or reintroduce human biases and mistakes. We develop new quasi-experimental tools to measure the impact of...

We show that intergenerational mobility changed rapidly by race and class in recent decades and use these trends to study the causal mechanisms underlying changes in economic mobility. For white children in the U.S. born between 1978 and 1992, earnings increased for children from high-income...

This paper develops a new test for identifying racial bias in the context of bail decisions - a high-stakes setting with large disparities between white and black defendants. We motivate our analysis using Becker's (1957) model of racial bias, which predicts that rates of pre-trial misconduct...

This paper connects changes in employer characteristics through job transitions to employee earnings following mergers and acquisitions (M&As). Using firm balance sheet data linked to individual earnings data in Canada and a matched difference-in-differences design, we find that after M&As...

A longstanding and influential view in U.S. correctional policy is that "nothing works" when it comes to rehabilitating incarcerated individuals. We revisit this hypothesis by studying an innovative law-enforcement-led program launched in the county jail of Flint, Michigan: Inmate Growth...

We investigate whether removing a previously-obtained criminal record improves employment outcomes. We estimate the causal impact of criminal record remediation laws that have been widely enacted with the goal of improving employment opportunities for millions of individuals with records. We...

We study the labor market impacts of retroactively reducing felonies to misdemeanors in San Joaquin County, CA, where criminal justice agencies implemented Proposition 47 reductions in a quasi-random order, without requiring input or action from affected individuals. Linking records of...

We develop new quasi-experimental tools to measure racial discrimination, due to either racial bias or statistical discrimination, in the context of bail decisions. We show that the omitted variables bias in observational release rate comparisons can be purged by using the quasi-random...